Modeling of Healthcare Facility Maintenance Staff Using Publicly Reported Hospital Metrics

Abstract

Operational staffing is an ongoing concern for the built environment industries. The proper staffing of maintenance personnel at hospital facilities to ensure optimal operations in the event of emergencies and disasters is an issue that has been the focus of continuing research. While a fair amount of scholarship has been dedicated to healthcare staffing in hospitals, such as nursing, there is a lack of research on identifying proper staffing for facility management related professions in hospital facilities. Numerous utilization metrics, such as admissions, and facility metrics, such as Gross Square Feet (GSF), have been proposed as potential predictive measures for making staffing allocations. This study was conducted to identify predictors of maintenance Full Time Equivalents (FTEs) using publicly published data by the Washington State Department of Health. A linear regression was performed on maintenance FTEs at these healthcare facilities using the predictor variables, GSF, admissions, available beds, and Plant, Property, & Equipment (PPE), R2 = .625, F (3,84) = 46.59, p = .000. This research suggests that benchmarking efforts can be supplemented through regularly published hospital data to utilize a wide variety of predictor variables. Future research should focus on developing models that can be applied at a national level.

Facility engineering staff benchmarking for workforce modeling at veterans health administration

“…The few available FE staffing benchmarks that are publicly available are based primarily on GSF. Although GSF is a commonly used metric in facility management, there may be other factors with stronger associations to staffing levels in health care and the VHA (Dodd et al, 2021). The Committee on Facilities Staffing Requirements for VHA addressed this issue by proposing that several additional factors be considered when developing a methodology for overall FE staffing levels and job-type mix, although no statistical evaluations were performed.…”